Sentence examples for by the background model from inspiring English sources

After controlling for background variables, the curriculum variables explained an additional 2.4%% of the variance in latent QLT scores relative to the variance explained by the Background Model.

Compared with the amount of variance in QLT scores explained by the Background Model, the amount of additional variance explained by the Curriculum Model was relatively low, and its practical significance should be considered with caution.

This state can be reached as well by pixels belonging to the background scene being affected by spurious noise not characterized by the background model,   (2) (PAP), partially absorbed pixel,.

The combination of the foreground masks obtained from the subtraction of two background models was already used by [6] in order to quickly adapt to changes in the scene while preventing foreground objects from being absorbed too fast by the background model.

The confidence value assigned to each observation sequence, Conf O), depends on: (1) the probability assigned by the mine model, P r(O|λ m ); (2) the probability assigned by the background model, P r(O|λ c ); and (3) the optimal state sequence.

The confidence value assigned to each observation sequence, Conf O), depends on: (1) the probability assigned by the mine model (λ m ), Pr(O|λ m ); (2) the probability assigned by the background model (λ c ), Pr(O|λ c ); and (3) the optimal state sequence.

Such background estimation and adaptation system discriminates interesting foreground objects from the uninteresting background by building the background model of the image [15, 16].

In this way, they were able to control how fast static objects get absorbed by the background models and detect them as those groups of pixels classified as background by the short-term but not by the long-term background model.

Notably, however, these values were often markedly higher than those suggested by the background models of the algorithms, supporting the earlier observation that especially the Poisson-based randomization model can severely underestimate the FDRs [ 22].

Whether an observed measurement was generated by the signal or the background model is determined by the assignment of a matching binary noise variable, which is generally unknown (i.e. hidden).

First, the shadow model is initialized directly from the background model by linearly attenuating the RGB values of background samples.